relational databases

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I always thought it was so interesting how when you are surfing the internet and an extremely relevant ad is on the side of the page or even on your Facebook newsfeed. One day I was searching for a very specific pair of shoes and literally searched every popular shoe site. After finding the shoe, I decided to think on it before committing. For a little while after that I would see these shoes on different sites, being advertised at discounted prices. These ads eventually helped me decide to buy the shoes and where to buy them from. This is known as re-marketing and has been proven to be successful and pulling in customers to finally make that purchase. Research shows that only 2% of potential customers make purchases on their first visit. This re-marketing technique keeps their interest and helps convert that other 98%.

Google has some marketing programs that help do just that. It is estimated that Google reaches about 80% of all web users, making their programs the optimal choice for marketing strategies. One of their most popular programs is AdWords. Using AdWords, users can can tag certain pages of their site that visitors have browsed and create a campaign to reserve relevant ads that as the visitor goes to different sites. Google originally implemented this system on MySQL database engine, moved it to Oracle, and then switched it back to MySQL due to speed issues. Eventually they developed a custom distributed Relational Database Management System known as Google F1, specifically for their Ad programs. F1 is a hybrid database that combines high availability, the scalability of NoSQL systems, and the consistency and usability of traditional SQL databases. F1 is built on Spanner, which helps provide the scalability necessary that enables you to store a few trillion database rows in millions of nodes distributed to hundreds of data centers. The database not only supports the ads, but also the all of the support systems Google offers with its programs.